Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use SiddharthaM/mdeberta-hate-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiddharthaM/mdeberta-hate-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SiddharthaM/mdeberta-hate-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SiddharthaM/mdeberta-hate-final") model = AutoModelForSequenceClassification.from_pretrained("SiddharthaM/mdeberta-hate-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SiddharthaM/mdeberta-hate-final: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/SiddharthaM/mdeberta-hate-final/resolve/main/training_args.bin
- Command line
-
hf download hf://SiddharthaM/mdeberta-hate-final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SiddharthaM/mdeberta-hate-final/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 9338f561bbc0b45f75b4d7e1839bccc591db874e6213d2c2e5f3489dabb8261b
- Size of remote file:
- 3.38 kB
- SHA256:
- 75221f66fe2ab8f57c74bc3812c62824de1586b212f2f808f7c737991669b4c4
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